Title: Multi-objective fuzzy optimisation method for emergency evacuation based on hybrid intelligence algorithm under fuzzy environment

Authors: Changxi Ma; Yinzhen Li; Ruichun He; Fang Wu; Li Sun; Bo Qi

Addresses: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China ' School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou City, Gansu Province, 730070, China

Abstract: After a sudden public event, how to optimise emergency evacuation routings and enhance the response capability of emergency system is an important issue for emergency management agency. In this paper, we choose the optimal evacuation routing under fuzzy environment to make sure the injured reach the destination safely and quickly. Chance-constrained programming model of emergency evacuation routings and chance-dependent constraint programming models are setup respectively and a hybrid intelligence algorithm is designed to solve the model. The algorithm, which combines simulation technique and the genetic algorithm, produces chromosomes according to priority-based coding mode, uses simulation technique to calculate target values of chromosomes, produces a new group by using improved roulette wheel method to select chromosomes, crosses by adopting the partially matched crossover method, and uses reciprocal exchange mutation method to mutate. Finally, an example is presented to validate the feasibility of this model and the algorithm. The research result can help emergency decision-makers to find an optimal route after a sudden public event and reduce the casualties caused by transportation delays.

Keywords: hybrid intelligence; fuzzy optimisation; emergency evacuation; fuzzy logic; genetic algorithms; evacuation routing; emergency response; emergency management; chance-constrained programming; simulation; optimal routes; transport delays.

DOI: 10.1504/IJCAT.2013.052799

International Journal of Computer Applications in Technology, 2013 Vol.46 No.3, pp.228 - 235

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 23 Mar 2013 *

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